In wireless communication systems utilizing multiple antennas at both transmitter and receiver, commonly known as Multiple-Input Multiple-Output (MIMO) systems, it is well known in background art that the performance is greatly enhanced if linear MIMO precoding can be used at the transmitter side. Such linear precoding has been implemented in the IEEE 802.16-2005 Standard and is also suggested for 3GPP E-UTRA.
Orthogonal Frequency Division Multiplexing (OFDM) combined with MIMO enables an extension of the MIMO precoding to frequency selective MIMO channels. In MIMO-OFDM, a broadband channel is converted into multiple narrowband channels corresponding to OFDM subcarriers. Each narrowband channel can be assumed to be flat fading.
Furthermore, equal size groups of adjacent OFDM subcarriers are formed to obtain OFDM sub-bands. A common value, used in 3GPP E-UTRA, is 25 adjacent OFDM subcarriers which form an OFDM sub-band. Hence, the total bandwidth is divided into K sub-bands. The width of each sub-band is chosen so that the channel is approximately flat fading within each sub-band. This implies that the same best precoding matrix is approximately valid for all subcarriers within a sub-band.
A problem arising in MIMO-OFDM is that due to frequency selective scheduling, the feedback overhead increases since the channel quality becomes a function of a number of OFDM sub-bands. In addition, when codebook based linear MIMO preceding is applied, the receiver needs to indicate the precoding matrix index (PMI) to the codebook for each OFDM sub-band as well. This means that the signaling overhead burden becomes significant and methods must be found to reduce this overhead.
For codebook based precoded MIMO-OFDM, some background arts exist, which all exploit the correlation of optimal preceding matrices on adjacent subcarriers or sub-bands to reduce the feedback of precoding information.
At the end of this specification, a number of background art documents are listed.
In document [6] “3GPP R1-061441, Feedback Reduction for Rank-1 Pre-coding for E-UTRA Downlink, Texas Instruments, Shanghai, May 2006” and document [7] “3GPP R1-061439, Evaluation of Codebook-based Precoding for LTE MIMO Systems, Texas Instruments, Shanghai, May 2006”, a grouping approach is described where the feedback of precoding information is reduced by creating larger groups of adjacent subcarriers and finding a precoding matrix which is valid on average for this larger group. For instance, it is recommended in document [6] that a precoding matrix index for every second OFDM sub-band is sufficient with only a small degradation in performance compared to feeding back a precoding matrix index for every OFDM sub-band. In this way the feedback overhead for the precoding matrix is halved.
The same basic approach is taken in document [3] “J. Choi, R. W. Heath Jr., Interpolation Based Unitary Precoding for Spatial Multiplexing MIMO-OFDM with Limited Feedback, IEEE Globecom Conference 2004, Dallas, USA, November 2004, page 214-218)” and document [4] “(J. Choi, R. W. Heath Jr., Interpolation Based Transmit Beamforming for MIMO-OFDM with Limited Feedback, IEEE Transactions on Signal Processing, Vol. 53, No. 11, November 2005, page 4125-4135”. The authors here suggest reporting precoding matrix indices for every L:th OFDM subcarrier, uniformly sampled over the whole bandwidth. In the transmitter, a reconstruction of the intermediate precoding matrix indices is performed using interpolation.
In document [5] “B. Mondahl, R. W. Heath Jr., Algorithms for Quantized Precoding in MIMO-OFDM Beamforming Systems, Proceedings of the SPIE, Volume 5847, pp. 80-87, 2005”, an alternative approach is suggested, where the channel information (precoding matrix information) is quantized in the time domain, instead of the frequency domain, where the transform decorrelates the channel information. The idea is to decorrelate the precoding matrix information before quantization. The performance of this method is shown to be similar to the grouping proposal in document [4].
The background art precoding matrix index feedback signaling reduction methods all have the disadvantage that they often feed back information that is not used at a transmitting end of the system. The background art solutions for reducing the precoding matrix index feedback overhead do not take into consideration that some information is more valuable than other information at the transmitting end.
There is thus a need for a method that intelligently chooses which information to feed back so as to further reduce the amount of precoding matrix index feedback signaling overhead.